High Accuracy Leak Detection Performed on Entire Live Wellbore in Real Time Using Fiber-Optic Diagnostic-Capable Coiled Tubing

McCarthy, Caitlin; Williams, Troy; Butz, Stephen

doi:10.2523/iptc-19576-ms

Cited by 3 publications

(1 citation statement)

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“…Over the past five years, several publications have covered overviews and case histories regarding this topic (Daneshy 2015;King and Valencia 2016;Adams et al 2017;Barreda et al 2018;Yu et al 2019;Casero and Rylance 2020). Other authors focused on technologies used to detect and quantify casing failures (Hamilton and Pattillo 2019;McCarthy et al 2020;Robertson et al 2020). Additional papers have focused on the cause of casing deformations and failures (Denny 2012;Haghshenas 2017;Mazhar and Ighalo 2018;Robinson et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Identifying Casing Failures with Signature Fracturing Treatment Pressure Behavior

Hoffman¹,

Wolfbrandt²,

Iriarte³

et al. 2020

Day 3 Wed, October 28, 2020

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One of the challenges of unconventional resource development is the identifying and preventing casing failures caused by the hydraulic fracturing process. Multiple mechanisms may be responsible for casing deformation and/or failures, starting with the rock properties of the formation, the wellbore configuration, quality control of tubulars, and operational aspects during drilling and completion. This paper presents two case studies where casing issues were discovered during the drill out of frac plugs following multi-stage fracturing treatments. The objectives of these studies are (a) to determine the cause and nature of the casing failures, (b) to recommend changes to future completion programs to prevent similar operational issues, and (c) to develop a model that automatically identifies these failures. The subject wells are located in two very different basins: the Eagle Ford trend in the Brazos Valley (BV) area of south Texas and the Powder River Basin (PRB) in Wyoming. In both studies, the casing issues could be directly correlated to Abnormal Pressure Behaviors (APBs) observed during fracturing. A total of 486 stages, completed in 12 different wells, were reviewed using a cloud-based application that allows stages to be examined individually, or as groups. Since then, five additional wells have been added to the data set. After problem stages were identified, the completion team worked with the drilling engineers and geologists to determine the mechanisms causing the casing damage. Tight spots encountered during frac plug drill out in the BV wells directly correlated with stages completed in geological transition zones between the Eagle Ford and Woodbine formations. Once this was recognized, the team implemented operational contingencies to fracture designs for stages completed in BV transition zones. In the PRB wells, after reevaluating the post-mill inspection of the casing, the damage was found to be poor casing quality control. The location of casing deformations and/or failures directly correlated with stages that displayed evidence of frac plug failure. Moving forward, the PRB completion supervisors were made aware of potential issues, and alternative procedures were developed for both fracturing and drill out operations that utilized the questionable casing. As of this time, no additional casing issues have occurred. In these studies, identification of the problem stages was initially performed manually (stage-by-stage) using a cloud-based analytics platform (CBAP). During the process, it was recognized that the two types of problem stages had their own characteristic pressure signature. A machine learning algorithm was developed that automatically identifies plug failure, which is indicated by a sudden unexplained pressure drop in the absence of rate changes. Transition stages could be easily identified through the use of stage variance plots (e.g., comparing maximum/average rates and pressures across multiple stages and wells) and also through machine learning algorithms that identified unexpected pressure increases followed by sharp pressure drops.

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Section: Introductionmentioning

confidence: 99%

Identifying Casing Failures with Signature Fracturing Treatment Pressure Behavior

Hoffman¹,

Wolfbrandt²,

Iriarte³

et al. 2020

Day 3 Wed, October 28, 2020

View full text Add to dashboard Cite

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A Literature Review

Li¹,

Karrenbach²,

Ajo‐Franklin³

2021

Geophysical Monograph Series

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Recent Advances in Downhole Fiber Optics Modeling & Analytics: Case Studies

Bale

Satti

Failla

et al. 2021

SPE Western Regional Meeting

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In recent years, the upstream oil and gas industry has witnessed significant breakthroughs in developing and deploying permanent, on-demand, and distributed temperature (DTS) and acoustic (DAS) fiber-optic monitoring systems to optimize well completions and enhance production. Beyond steady advances in hardware, challenges associated with the analysis of distributed optical data are being addressed to enable delivery of value-driven answer solutions and services. Such solutions are often nontrivial and must be driven by scientific workflows in which data-driven models, advanced analytics and most importantly, physics-based models are applied at the right scale to correlate the data to downhole events. In this study, we present a methodology for integrating state-of-the-art intelligent completion and production tools together with a robust modeling and analytics framework for the efficient development of data interpretation services for complex downhole environments. The answer product platform discussed is built on fast computational models, robust data-driven analytics, cloud-based data streaming and management services, and real-time reporting delivery systems. Several case-studies demonstrate how our fiber-optics solutions and analysis are leveraged for applications such as leak detection, fluid injection profiling, acid placement, sand detection, and water ingress. For each case-history, we discuss the operational workflow for the downhole intelligent assembly, procedures for acquiring high-resolution DTS/DAS data, and the use of advanced fast physics or data driven models used to deliver the solution. Some of the application examples (e.g. water ingress and sand detection) also demonstrate how simultaneous measurements of DTS and DAS data are often critical to detecting and devising a strategy for mitigating well-specific issues. The case-studies presented in this study demonstrate how vast amounts of data can be acquired by fiber-optic interrogation systems and subsequently interpreted in real-time, or near real-time. Such a process is enabling oil and gas operators to make data-driven decisions that drive optimized reservoir performance and proactively mitigate operational risk such as NPT due to equipment failure.

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High Accuracy Leak Detection Performed on Entire Live Wellbore in Real Time Using Fiber-Optic Diagnostic-Capable Coiled Tubing

Cited by 3 publications

References 1 publication

Identifying Casing Failures with Signature Fracturing Treatment Pressure Behavior

Identifying Casing Failures with Signature Fracturing Treatment Pressure Behavior

A Literature Review

Recent Advances in Downhole Fiber Optics Modeling & Analytics: Case Studies

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